At a Glance
- Tasks: Lead data science projects in the public sector, showcasing AI and machine learning solutions.
- Company: Join a debt-free, multi-billion-dollar leader in data and AI, on the path to IPO.
- Benefits: Enjoy flexible work options, ongoing training, and wellness programs to support your well-being.
- Why this job: Make a real impact in public sector transformation while growing your skills in a diverse environment.
- Qualifications: 6 years of experience in data analysis; BSc/MSc in a quantitative field; Security Clearance required.
- Other info: Contribute to thought leadership through blogs and public speaking opportunities.
The predicted salary is between 43200 - 72000 £ per year.
We’re a leader in data and AI. Through our software and services, we inspire customers around the world to transform data into intelligence – and questions into answers.
We’re also a debt-free multi-billion-dollar organization on our path to IPO-readiness. If you’re looking for a dynamic, fulfilling career coupled with flexibility and world-class employee experience, you’ll find it here.
About the job
The Customer Advisory team is looking for a Data Scientist with a strong track record in Public Sector engagements. The role requires Security Clearance (To gain Security Clearance you will normally need to have been a UK resident for a minimum of 5 years) and involves leading customer-facing technical engagements across data science, machine learning, and AI within the UK public sector and defence sectors.
As a Data Scientist , you will:
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Customer-Focused Data Science Leadership:
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Lead technical Proof of Concepts (PoCs), demonstrations, and MVPs to showcase advanced data science solutions.
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Deliver impactful, hands-on AI and machine learning projects that drive tangible value for public sector clients.
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Serve as a subject matter expert (SME) for data science in commercial opportunities, marketing, and customer success.
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Technical Delivery:
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Develop end-to-end data science solutions using tools such as SAS Viya, Python, and R.
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Build, train, and deploy predictive and prescriptive models addressing challenges like rare-event detection, workforce attrition, and operational efficiencies.
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Collaboration & Mentoring:
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Act as a technical mentor to upskill junior team members, fostering collaboration and best practices.
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Work cross-functionally with customer advisory, sales, and customer success teams to ensure technical excellence.
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Innovation & Problem-Solving:
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Prototype and implement novel solutions to complex challenges, ensuring explainability and performance improvements.
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Stay abreast of advancements in AI tools to deliver cutting-edge solutions.
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Thought Leadership:
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Represent the organization as a data science leader through blogs, public speaking, and industry events.
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Support public outreach initiatives that promote the role of data science and AI., * Opportunities to lead in cutting-edge projects for public sector transformation.
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Ongoing technical training and development opportunities.
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Our Recreation and Fitness center offers recorded fitness classes to help you fit movement into your day.
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Your well-being matters, and that’s why we support all dimensions of your well-being by offering programs that reduce stress and distractions to help you remain healthy and productive., At SAS, it’s not about fitting into our culture – it’s about adding to it. We believe our people make the difference. Our diverse workforce brings together unique talents and inspires teams to create amazing software that reflects the diversity of our users and customers. Our commitment to diversity is a priority to our leadership, all the way up to the top; and it’s essential to who we are. To put it plainly: you are welcome here.
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Six years of relevant experience such as analyzing data and/or building analytical models.
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BSc (MSc preferred) in Data Science, Mathematics, Computer Science, Economics, or a related quantitative discipline.
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Equivalent combination of education, training and experience may be considered in place of the above qualifications.
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Security Clearance (SC) or eligibility to obtain SC clearance.
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Technical Expertise:
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Advanced proficiency in SAS Viya, Python, and R.
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Experience with machine learning, predictive modelling, and statistical methods.
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Strong data visualization skills.
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Public Sector Experience: Minimum 3+ years delivering data science solutions for UK public sector or defence clients.
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Communication Skills: Excellent ability to explain complex data science solutions to non-technical stakeholders.
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Problem Solver: Proven ability to develop innovative solutions to challenging problems.
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You’re curious, passionate, authentic and accountable. These are our values and influence everything we do.
Preferred Qualifications
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Previous contributions to public thought leadership or technical blogs.
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Background in mentoring or technical leadership roles.
SAS only sends emails from verified "sas.com" email addresses and never asks for sensitive, personal information or money. If you have any doubts about the authenticity of any type of communication from, or on behalf of SAS, please contact Recruitingsupport@sas.com.
LI-FP1
SAS
Data Scientist - Public Sector employer: SAS
Contact Detail:
SAS Recruiting Team
Recruitingsupport@sas.com
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Public Sector
✨Tip Number 1
Make sure to highlight your experience in the public sector during networking events or conversations. This role specifically requires a strong track record in public sector engagements, so sharing relevant projects or insights can set you apart.
✨Tip Number 2
Engage with communities and forums focused on data science and AI in the public sector. This will not only help you stay updated on industry trends but also connect you with potential colleagues and mentors who can provide valuable insights.
✨Tip Number 3
Consider attending industry conferences or workshops where you can showcase your expertise in data science and machine learning. This visibility can lead to opportunities and connections that may help you land the job.
✨Tip Number 4
Stay informed about the latest advancements in AI tools and techniques. Being able to discuss recent innovations and how they can be applied to public sector challenges will demonstrate your commitment and knowledge during interviews.
We think you need these skills to ace Data Scientist - Public Sector
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in data science, particularly within the public sector. Emphasize your technical skills in SAS Viya, Python, and R, as well as any specific projects that demonstrate your ability to deliver impactful solutions.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data science and AI, and how it aligns with the company's mission. Mention your experience with public sector clients and your ability to communicate complex concepts to non-technical stakeholders.
Showcase Your Thought Leadership: If you have contributed to blogs or spoken at industry events, include this in your application. Highlighting your thought leadership can set you apart and demonstrate your commitment to the field of data science.
Prepare for Technical Questions: Be ready to discuss your technical expertise in detail during the interview process. Prepare examples of past projects where you used machine learning and predictive modeling to solve real-world problems, especially in the public sector.
How to prepare for a job interview at SAS
✨Showcase Your Public Sector Experience
Make sure to highlight your previous work in the public sector during the interview. Discuss specific projects where you delivered data science solutions and how they impacted the organization.
✨Demonstrate Technical Proficiency
Be prepared to discuss your experience with SAS Viya, Python, and R. You might be asked to explain how you've used these tools in past projects, so have examples ready that showcase your technical skills.
✨Communicate Complex Ideas Simply
Since you'll need to explain complex data science concepts to non-technical stakeholders, practice simplifying your explanations. Use analogies or real-world examples to make your points clear and relatable.
✨Emphasize Collaboration and Mentoring
Talk about your experience working cross-functionally and mentoring junior team members. Highlight any specific instances where you fostered collaboration or shared best practices within your team.